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Prehospital personnel in Emergency Medical Service (EMS) systems have varying levels of accuracy in stroke recognition. Identifying the accuracy of emergency medical dispatcher using Medical Priority Dispatch Systems (MPDS) stroke protocol and paramedics may help understand the accuracy of stroke recognition in about 3000 emergency medical dispatch systems and prehospital systems world wide.Our aim was to assess the accuracy of stroke identification in emergency medical dispatchers (EMD) with high compliance to MPDS protocol and paramedics using Cincinnati Prehospital Stroke Scale (CSS).This was a retrospective observational study. Data was acquired from a computer assisted dispatch (CAD) system, a computerized paramedic record database and discharge diagnosis from billing records or stroke registry containing all stroke assessments of patients who presented to the participating study hospitals within 12 hours of symptom onset. We included patients 18 years or older, identified as having stroke by EMD and city agency paramedics. We excluded patients taken to hospitals not participating in the study, patients with a dispatch determinant of Stroke (card 28) not transported by City EMS agency (SDMSE) to participating hospitals, patients in the stroke registry not transported by SDMSE or patients with no final outcome data. A stroke neurologist or hospital discharge diagnosis of stroke (physician diagnosis) was used to determine the sensitivity and predictive values of EMD and paramedic recognition of stroke.Of 882 patients with a dispatch determinant of stroke using MPDS Stroke protocol, 367 had a final discharge diagnosis of stroke. This gives a sensitivity of 83% and a positive predictive value of 42% for EMD using MPDS Stroke protocol. Of 477 patients with a paramedic assessment of stroke using CSS, 193 had a final discharge diagnosis of stroke. This gives a sensitivity of 44% and a PPV of 40% for paramedics using CSS.In our EMS system, EMD using MPDS Stroke protocol with a high compliance has a higher sensitivity than paramedics using CSS.

Objective Several neuroimaging studies have examined language reorganization in stroke patients with aphasia. However, few studies have examined language reorganization in stroke patients without aphasia. Here, we investigated functional connectivity (FC) changes after stroke in the language network using resting-state fMRI and performance on a verbal fluency (VF) task in patients without clinically documented language deficits. Methods Early-stage ischemic stroke patients (N = 26) (average 5 days from onset), 14 of whom were tested at a later stage (average 4.5 months from onset), 26 age-matched healthy control subjects (HCs), and 12 patients with cerebrovascular risk factors (patients at risk, PR) participated in this study. We examined FC of the language network with 23 seed regions based on a previous study. We evaluated patients' behavioral performance on a VF task and correlation between brain resting-state FC (rsFC) and behavior. Results Compared to HCs, early stroke patients showed significantly decreased rsFC in the language network but no difference with respect to PR. Early stroke patients showed significant differences in performance on the VF task compared to HCs but not PR. Late-stage patients compared to HCs and PR showed no differences in brain rsFC in the language network and significantly stronger connections compared to early-stage patients. Behavioral differences persisted in the late stage compared to HCs. Change in specific connection strengths correlated with changes in behavior from early to late stage. Conclusions These results show decreased rsFC in the language network and verbal fluency deficits in early stroke patients without clinically documented language deficits.

Introduction: Brain-computer interface (BCI) is an emerging technology for stroke rehabilitation, but little is known about brain changes associated with its use. We examine changes in laterality index (LI) and functional connectivity (FC) during hand movements associated with BCI interventional therapy. Methods: We collected anatomical and functional MRI of 8 stroke patients with upper extremity motor impairment before, during, and after up to 6 weeks of therapy using a BCI system with tongue and functional electrical stimulations. We acquired functional images during imagined (MI) and executed (ME) tapping and squeezing of each hand; not all subjects performed all tasks. Two subjects’ scans were flipped so that as a group the lesion was left (L) and the impaired limb right (R). We computed LI using 3 mask sets: whole brain, motor network, and motor cortex. Group-level analyses examined FC changes to motor network seeds using AFNI and Matlab NBS toolbox. Results: BCI intervention led to decreased average LI during tapping. Overall, R taps shifted L to bilateral; all L taps shifted bilateral to R. Trends were consistent across all masks at thresholds p Conclusions: BCI interventional therapy of the impaired hand leads to more bilateral brain activity, while more lateralized activation was seen of the unimpaired hand to its corresponding contralateral motor regions. With different patterns of change observed during tasks using the impaired or unimpaired hand, lesioned brain areas may respond differently to BCI than unlesioned counterparts.

BACKGROUND: The objective of this study is to investigate the brain activation patterns and relationship with verbal fluency performance in stroke recovery. METHODS: Patients with ischemic stroke (N=19, mean age =64, 7F) and 17 healthy age-matched controls, participated in the study. Measures on a verbal fluency task were collected outside the scanner. Functional MR images were collected as subjects performed the same task(3T GE scanner). Task included alternating 20 second blocks of rest and word retrieval given a letter. Results from 19 acute patients(< 7 days from stroke onset - V1), of which 9 were also tested in the sub-acute stage(between 7 days and 6 months from stroke onset - V2), are reported here. RESULTS: Acute patients showed significantly greater activation in several regions, including the right middle and inferior frontal gyrus, and de-activations in regions including left middle temporal and frontal gyri(p CONCLUSIONS: Results suggest increased activation in acute stroke in right hemisphere language regions; healthy controls conversely show less activation in these regions. Additionally, activity in brain areas significantly correlated with behavior. Activation pattern in acute stroke however changes over time with patients in the sub-acute stage showing pattern similar to healthy controls. This is consistent with studies suggesting that activations in the acute stage tend to normalize over time likely due to areas prior to the stroke re-gaining function.

Objective: Stroke can have important effects on widespread brain regions resulting in network disruption. This study investigates the changes in spontaneous activity in the brain after stroke using resting-state functional connectivity(FC) MRI. Methods: Acute ischemic stroke patients (N=22, 11 cortical, mean age=60, 10F) were recruited within 7 days of stroke onset(timepoint 1, V1). Eleven of these patients were also scanned at timepoint 2(V2), approximately 3 months later. Age-matched healthy controls (N=17, mean age = 56, 7F) and 7 patients with risk factors for stroke (mean age=67, 1F) were also recruited in the study. Ten minute eyes-closed resting-state fMRI scans were collected along with a high resolution anatomical scan. We examined FC in the language network consisting of ten regions extracted based on functional activations on a phonemic fluency task performed during a separate scan. We also examined the correlation of brain FC with behavioral performance on the task outside the scanner. Results: We examined correlation between every seed region and every other region in the network(45 seed region-pairs). Compared to age-matched controls, acute strokes showed significantly reduced inter-hemispheric connectivity, specifically between inferior frontal and temporal regions(p Conclusions: These results suggest that acute strokes show reduced brain connectivity between contralateral regions in the language network; however, this connectivity pattern is restored in the sub-acute stage.

Background: Resting-state fMRI (rs-fMRI) has been used for assessing task-free brain activity changes after stroke. One prominent resting-state neural network is the default mode network (DMN) that has been suggested to be suppressed during cognitive tasks. Older adults often show difficulties in suppressing DMN compared to younger adults during cognitive task performance. Moreover, dysfunction of DMN appears to be linked with the severity of post-stroke depression. Here we explored brain plasticity changes in DMN in stroke subjects. Methods: 9 stroke subjects (mean age=60.3, 5 Male) and 5 normal healthy subjects (mean age=48, 4 Male) underwent two rs-fMRI scans. Patients participated in the 1st scan within 7 days after onset and within 6 months (mean ~3 months) postonset in the 2nd scan. Brain plasticity changes were examined by functional connectivity measures that were computed using region-of-interest analysis. Rs-fMRI data were pre-processed in AFNI. The resulting time-series from 6 common seeds in DMN were averaged over each seed and correlated with that from every other seed to generate the Pearson correlation coefficients. These correlations were then z-transformed representing the 15 unique functional connections (fconn) in DMN. Fconn changes were determined with intraclass correlation (ICC), which measures reproducibility of fconn between scans. A reliable connection, as suggested to be an ICC ≥ 0.5, requires a small within-subject plasticity change compared to the between-subject variance. Results: Shown in Table 1. Conclusion: As seen from Table 1, fconn between RtLatPar and PC may undergo plasticity changes after stroke (ICC < 0.5) as would be reliable in the normal group. Fconn between LtLatPar and PC, mPFC and PC, right and left LatPar were found to be significant and reliable, which could be due to less suppression in DMN and higher between-subject variability after stroke.

Stroke is common, with a high rate of disability and death, and current therapies are both highly time sensitive and carry some risk, making rapid diagnosis important. Many cases of stroke are difficult to diagnose clinically during the acute phase, and there are limitations to the ability of diagnostic imaging to help with the necessary speed. A reliable and valid biomarker would be invaluable for this common clinical situation, as it has been with myocardial infarction. A large number of molecules have been evaluated for this role, both in the laboratory and in patients, but the results to date have been disappointing. In this article, we review the operative concepts in the search for a diagnostic biomarker of stroke, a few of the promising candidates and the current challenges to validation.

It is well established that several infectious diseases can directly lead to ischemic or hemorrhagic stroke during their course. It appears possible that common viral and bacterial infections can increase the susceptibility to stroke by promoting atherosclerosis, inflammation, and local thrombosis. Stroke commonly leads to disruption of protective mechanisms against infection and induces a cascade of anti-inflammatory and immunosuppressive reactions, which greatly increases the risk of infection. The social and economic costs of post-stroke infections and their impact on stroke morbidity and outcome are dramatic. Understanding the pathophysiologic links between stroke and infection is therefore of paramount importance, and effective preventive strategies to reduce the risk of infection are needed. This article summarizes current clinical and experimental data regarding the interactions between stroke and infection and outlines possible targets for therapeutic intervention.

Background: Ischemic stroke and transient ischemic attack can be difficult to diagnose clinically, and both acute and preventive therapies carry some risk. Serum biomarkers could increase diagnostic certainty by helping to distinguish cerebral ischemia from common mimics such as focal seizure, complicated migraine, and psychogenic spells. Biomarkers could also identify patients at high risk for future vascular events, which would aid in management decisions. Review Summary: There are many potential obstacles to finding these biomarkers, which are reviewed here, including the blood brain barrier, confounding by other conditions, and imperfect gold standards for use in validation. Diagnostic biomarkers are likely to be molecules found predominantly in brain tissue with rapid entry into the blood, whereas risk-stratification biomarkers may be related to the concept of an active atherosclerotic plaque. Many promising serum molecules have been examined in small series of patients with cerebrovascular disease. Conclusion: Large series examining many candidate molecules will be needed to find valid biomarkers, and this should be followed by use in future intervention trials to prove their utility.

Acute ischemic stroke (AIS) is a significant cause of death and disability in the United States. It has been 10 years since tissue plasminogen activator became the first medication approved by the US Food and Drug Administration for treatment for AIS. However, this treatment simply reopens arteries. The identification of deleterious cellular reactions that occur secondary to cerebral ischemia has led investigators to search for neuroprotection strategies to complement reperfusion. More than 100 human trials, including a handful of phase III trials, had failed to produce an efficacious neuroprotective agent. In 2006, the first positive trial of neuroprotection was published: the SAINT I (Stroke-Acute Ischemic NXY Treatment) study. In February 2008, the SAINT II study was published, indicating that NXY-059 was not effective for AIS treatment.